jacobian

commit 59271da9ceb7ddaa2475d924d0a763b9d8a450d9
parent 1f3f753317f0f5e2699b27a64fbff9e32d5e82af
Author: David Freifeld <freifeld.david@gmail.com>
Date:   Wed,  1 Jul 2020 16:17:15 -0700

Some W&B tweaks

Diffstat:
M
bpnn.cpp
 | 
14
++++++++------
M
bpnn.hpp
 | 
4
+++-
M
example.py
 | 
22
++++++++++++++++------
M
mr_bpnn_2.cpp
 | 
3
++-

4 files changed, 29 insertions(+), 14 deletions(-)
diff --git a/bpnn.cpp b/bpnn.cpp
@@ -274,8 +274,6 @@ float Network::test(char* path)
 
 void Network::train(int total_epochs)
 {
-  float epoch_cost = 1000;
-  float epoch_accuracy = -1;
   int epochs = 0;
   //printf("Beginning train on %i instances for %i epochs...\n", instances, total_epochs);
   double batch_time = 0;
@@ -293,18 +291,22 @@ void Network::train(int total_epochs)
       batches++;
       //t++;
     }
-    epoch_accuracy = 1.0/((float) instances/batch_size) * acc_sum;
-    epoch_acc = epoch_accuracy;
+    epoch_acc = 1.0/((float) instances/batch_size) * acc_sum;
     epoch_cost = 1.0/((float) instances/batch_size) * cost_sum;
-    printf("Epoch %i/%i - cost %f - acc %f\n", epochs+1, total_epochs, epoch_cost, epoch_accuracy);
+    printf("Epoch %i/%i - cost %f - acc %f\n", epochs+1, total_epochs, epoch_cost, epoch_acc);
     batches=1;
     epochs++;
     rewind(data);
   }
 }
 
-float Network::get_info()
+float Network::get_acc()
 {
   return epoch_acc;
 }
+
+float Network::get_cost()
+{
+  return epoch_cost;
+}
   
diff --git a/bpnn.hpp b/bpnn.hpp
@@ -39,6 +39,7 @@ public:
   int t;
 
   float epoch_acc;
+  float epoch_cost;
   float learning_rate;
   float bias_lr;
   int batch_size;
@@ -62,7 +63,8 @@ public:
   float test(char* path);
   void train(int total_epochs);
 
-  float get_info();
+  float get_acc();
+  float get_cost();
 };
 
 void demo(int total_epochs);
diff --git a/example.py b/example.py
@@ -4,20 +4,30 @@ import numpy
 import time
 
 batch_sz = 10
-layers = 1
+layers = 2
+epochs = 50
+lr = 0.0155
+bias_lr = 0.03
+neurons = 3
 
-net = mrbpnn.Network("./data_banknote_authentication.txt", batch_sz, 0.0155, 0.03)
+net = mrbpnn.Network("./data_banknote_authentication.txt", batch_sz, lr, bias_lr)
 net.add_layer(4, "linear")
 for i in range(layers):
-    net.add_layer(5, "relu")
+    net.add_layer(neurons, "lecun_tanh")
 net.add_layer(1, "resig")
 net.initialize()
 
 import wandb
 wandb.init(project="jacobian")
-wandb.config.update({"epochs": 50, "batch_size": batch_sz, "hidden_layers": layers})
-for i in range(50):
+wandb.config.update({"epochs": epochs,
+                     "batch_size": batch_sz,
+                     "learning_rate": lr,
+                     "bias_lr": bias_lr,
+                     "hidden_layers": layers,
+                     "activation":"lecun_tanh",
+                     "neurons": neurons})
+for i in range(epochs):
     net.train(1)
-    wandb.log({'accuracy': net.get_info()})
+    wandb.log({'accuracy': net.get_acc(), 'cost': net.get_cost()})
 
 wandb.save('jacobian.h5')
diff --git a/mr_bpnn_2.cpp b/mr_bpnn_2.cpp
@@ -119,5 +119,6 @@ PYBIND11_MODULE(mrbpnn, m) {
     .def("update_layer", &Network::update_layer, py::arg("vals"), py::arg("len"), py::arg("index"))
     .def("next_batch", &Network::next_batch)
     .def("train", &Network::train, py::arg("epochs"))
-    .def("get_info", &Network::get_info);
+    .def("get_acc", &Network::get_acc)
+    .def("get_cost", &Network::get_cost);
 }